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Altered functional connectivity in lesional peduncular
hallucinosis with REM sleep behavior disorder
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Citation: Geddes, Maiya R. et al. “Altered Functional Connectivity in Lesional Peduncular
Hallucinosis with REM Sleep Behavior Disorder.” Cortex 74 (January 2016): 96–106 © 2015
Elsevier
As Published: http://dx.doi.org/10.1016/j.cortex.2015.10.015
Publisher: Elsevier
Persistent URL: http://hdl.handle.net/1721.1/112160
Version: Author's final manuscript: final author's manuscript post peer review, without
publisher's formatting or copy editing
Terms of use: Creative Commons Attribution-NonCommercial-NoDerivs License

HHS Public Access
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Cortex. Author manuscript; available in PMC 2017 January 01.
Published in final edited form as:
Cortex. 2016 January ; 74: 96–106. doi:10.1016/j.cortex.2015.10.015.

Altered functional Connectivity in Lesional Peduncular
Hallucinosis with REM Sleep Behavior Disorder
Maiya R. Geddes, MD1,2,*, Yanmei Tie, PhD3, John D. E. Gabrieli, PhD1, Scott M. McGinnis,
MD2, Alexandra J. Golby, MD3, and Susan Whitfield-Gabrieli, PhD1
Yanmei Tie: ytie@bwh.harvard.edu; John D. E. Gabrieli: gabrieli@mit.edu; Scott M. McGinnis: sm93@partners.org;
Alexandra J. Golby: agolby@partners.org; Susan Whitfield-Gabrieli: swg@mit.edu

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1Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research,

Massachusetts Institute of Technology, Cambridge, MA, USA
2Brigham and Women’s Hospital, Division of Cognitive and Behavioral Neurology, Harvard

University, Boston, MA, USA
3Brigham and Women’s Hospital, Department of Neurosurgery, Harvard University, Boston, MA,

USA

Abstract

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Brainstem lesions causing peduncular hallucinosis (PH) produce vivid visual hallucinations
occasionally accompanied by sleep disorders. Overlapping brainstem regions modulate visual
pathways and REM sleep functions via gating of thalamocortical networks. A 66-year-old man
with paroxysmal atrial fibrillation developed abrupt-onset complex visual hallucinations with
preserved insight and violent dream enactment behavior. Brain MRI showed restricted diffusion in
the left rostrodorsal pons suggestive of an acute ischemic infarct. REM sleep behavior disorder
(RBD) was diagnosed on polysomnography. We investigated the integrity of ponto-geniculateoccipital circuits with seed-based resting-state functional connectivity MRI (rs-fcMRI) in this
patient compared to 46 controls. Rs-fcMRI revealed significantly reduced functional connectivity
between the lesion and lateral geniculate nuclei (LGN), and between LGN and visual association
cortex compared to controls. Conversely, functional connectivity between brainstem and visual
association cortex, and between visual association cortex and PFC was significantly increased in
the patient. Focal damage to the left rostrodorsal pons is sufficient to cause RBD and PH in
humans, suggesting an overlapping mechanism in both syndromes. This lesion produced a pattern
of altered functional connectivity consistent with disrupted visual cortex connectivity via deafferentation of thalamocortical pathways.

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1. Introduction
In two seminal papers, Norman Geschwind outlined a disconnection framework for
understanding the emergence of clinical syndromes from localized brain lesions
(Geschwind, 1965). This work along with contemporary connectionist theories (Catani &
ffytche, 2005) underscores the distributed network effects of focal brain injury (diaschisis).

*

Corresponding author mgeddes@mit.edu Telephone: (617) 324-3981, Fax: (617) 324-5311.

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A hodotopic model of visual hallucinations emphasizes dysfunction localized within specific
brain regions (topological) and aberrant connectivity between regions (hodological) (Catani
& ffytche, 2005; ffytche, 2008). Advances in human brain imaging, in particular restingstate functional connectivity MRI (rs-fcMRI), allow for the direct testing of atypical
functional connection in the living human brain.
Described by Lhermitte (1922), peduncular hallucinosis (PH) occurs with focal lesions of
the brainstem or thalamus (Benke, 2006). Here, we present a case study of a patient with a
brainstem stroke associated with new-onset PH and REM sleep behavior disorder (RBD).
RBD and visual hallucinations are important non-motor features of neurodegenerative
synucleinopathies including Parkinson’s disease (PD) and Lewy body dementia (LBD). The
association of these syndromes secondary to a brainstem lesion suggests that they share a
common underlying neural mechanism.

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Theoretical ‘release’ of visual association cortex is used to explain many forms of visual
hallucinations (Cogan, 1973; Jackson, 1879; Kinsbourne & Warrington, 1963; Lance, 1976;
Manford & Andermann, 1998; West, 1962). PH is hypothesized to result from brainstem
damage in regions that modulate lateral geniculate nucleus (LGN) (Manford & Andermann,
1998). Overlapping brainstem nuclei control thalamic state shifts and coordinate REM sleep
(McCarley, Benoit, & Barrionuevo, 1983; Manford & Andermann, 1998; Sherman, 2001).
Manford and Andermann (1998) proposed that in addition to causing sleep disturbance, a
brainstem lesion could produce complex visual hallucinations via thalamic inhibition by
impairing LGN transmission and reducing the fidelity of retino-geniculate-occipital
signaling.

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We focused our analysis on visual association, rather than calcarine, cortex based on the
results of intraoperative stimulation, functional neuroimaging, and primate anatomical
studies (ffytche et al., 1998; Foerster, 1931; Penfield & Perot, 1963; Sincich, Park,
Wohlgemuth, & Horton, 2004). During stimulation studies by Penfield and Perot (1963),
electric current applied to primary visual cortex produced formless “visual flashes and
coloured lights”, whereas stimulation of visual association cortex caused “an experiential
response”. Functional neuroimaging evidence also supports a key role of extrastriate cortex
in the generation of complex visual hallucinations (ffytche et al., 1998). Relatedly, LGN has
anatomical connectivity to extrastriate regions (e.g., V5) (Sincich, Park, Wohlgemuth, &
Horton, 2004) and aberrant function of the retino-geniculate-extrastriate pathway may
underlie certain types of visual hallucinations in PD (Diederich, Stebbins, Schiltz, & Goetz,
2014).

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To investigate the distributed, polysynaptic network impacts of the patient’s lesion, we
applied an inferentially powerful combined lesional-functional imaging approach. Based on
the Manford and Andermann (1998) model, we anticipated that there would be reduced
connectivity, a surrogate for thalamic de-afferentation, between left rostrodorsal pons and
LGN, and also between LGN and visual association cortex. In addition, we hypothesized
that disrupted thalamocortical circuitry facilitates emergence of experiential symptoms via
aberrant visual network reorganization. To test this hypothesis, we examined whole-brain
connectivity from visual association cortex in the patient compared to controls in order to

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identify brain regions with pathologically increased connectivity that might support the
subjective experience of hallucinations.

2. Report of a case

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A 66-year-old right-handed man with paroxysmal atrial fibrillation, hypertension, and
dyslipidemia underwent laparoscopic gastric bypass surgery. Anticoagulation was
discontinued prior to surgery. Perioperative course was complicated by a traumatic Foley
catheter placement, blood loss with a nadir in hemoglobin of 7.6 g/dL requiring transfusion,
and hypotension to 80/50 mmHg. On the first postoperative day he developed vivid,
complex visual hallucinations and violent dream enactment behaviors (DEB) with nocturnal
vocalizations. He remained completely lucid throughout his hospital course and responded
appropriately to questions; he recognized that his hallucinations were not real. Structural
brain MRI three days after the surgery showed restricted diffusion in the left rostrodorsal
pons suggestive of an acute ischemic infarct (Fig.1). There was no evidence of cortical
infarction on initial or follow up neuroimaging.

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The patient provided detailed descriptions of “visions and dreams”: he perceived moving
images of synchronized swimmers in colorful uniforms. He reported simple hallucinations
of “shapes on the wall, and colors and people [that] changed”. He experienced
metamorphopsias (visual distortions): the floor appeared uneven, clocks and pictures on the
wall were distorted and seemed to grow and shrink. He perceived pink and yellow-tinted
elementary geometric shapes that morphed from squares to triangles and fluctuated in size.
His visions occurred throughout the day, without diurnal variation or hypnogogic/
hypnopompic onset. Emotional content of the visual imagery was mildly disturbing. The
hallucinations improved and by the fourth postoperative day he saw only simple
hallucinations that worsened at the end of the day; he described red moving dot photopsias,
“squiggly lines”, and brown puffs of smoke.

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The patient did not have fluctuations in arousal or attention. He was consistently oriented to
time and place, correctly spelled ‘world’ backwards and listed months of the year
backwards. His digit span forward was seven, and backwards span was four. Speech was
fluent without paraphasic errors or word finding difficulty. Repetition, comprehension and
performance on the Boston naming test (Kaplan, Goodglass, & Weintraub, 1983) were
intact. His writing was normal, without micrographia. Memory registration and recall were
intact. The patient had normal praxis. Evaluation in neuro-ophthalmology showed intact
visual acuity and correct identification of color plates with each eye separately. Visual fields
were normal on confrontation and Humphrey automated perimetry. Basic visuoperceptual
function was also intact: he performed normally on the Benton visual form discrimination
test (Benton, Sivan, Hamsher, Varney, & Spreen, 1994) and the Hooper visual organization
test (Hooper, 1958).
At three-year follow up, the patient had persistent perceptual symptoms. He experienced
multiple daily fleeting “shadows” in his peripheral vision in all lighting environments
(sensation de passage); he had insight into the unreality of these hallucinations, but was
unable to suppress a reflexive lateral saccade towards these apparitions when they occurred.

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He also reported visual misattributions (pareidolias). For example, he mistook fire hydrants
for human forms but rapidly self-corrected his perceptual errors. In dim lighting, he
experienced visual illusions with preserved insight. For example, he perceived “little insects”
crawling over the carpet and “grasshoppers” on the toilet brush at night. The patient also
reported difficulty tracking a golf ball after hitting it.

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Serial comprehensive neurological examinations were unremarkable and unchanged at
symptom onset and throughout 40 months of follow up. Cranial nerve exam was normal. In
particular, visual fields were full on confrontation and there was no extinction to
simultaneous visual stimuli. Range of eye movements was normal on saccades and smooth
pursuit. Motor exam, sensation, reflexes, coordination and gait were normal. There was no
retropulsion on pull testing. The patient did not have extrapyramidal signs: at 27 months
post-stroke, he scored 2 (for diminished leg agility secondary to bilateral knee replacement)
on the MDS unified Parkinson’s disease rating scale (UPDRS), Part III (motor examination)
(Movement Disorder Society Task Force, 2003). At 40-months, the patient’s Hoehn and
Yahr stage was zero (Hoehn & Yahr, 1967) and disability as measured by the modified
Rankin scale (mRS) was 1 (out of 6) (Bonita & Beaglehole, 1988; Rankin, 1957).

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Immediately after hospital discharge, the patient’s spouse reported DEB during the second
half of the night. While asleep, he inadvertently struck his wife and yelled profanities. At
symptom onset, he had taken citalopram for three years to treat adjustment disorder;
citalopram was discontinued in hospital. The patient had obstructive sleep apnea for over ten
years and was compliant with continuous positive airway pressure (CPAP) therapy.
Symptoms of sleepwalking, hypnogogic hallucinations, sleep paralysis, and cataplexy were
absent. He reported daily bowel movements and lacked symptoms suggestive of autonomic
dysfunction. DEB persisted and was refractory to treatment with melatonin 12 mg and
clonazepam 2 mg. REM sleep without atonia (RSWA) was observed on two in-hospital
polysomnography studies (Fig. 2) consistent with a diagnosis of RBD. EEG did not show
epileptiform activity.

3. Methods
3.1. Polysomnography and Parasomnia Diagnostic Parameters

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Long-term video-EEG polysomnography was performed in the hospital using a Polysmith
Nihon Kohden system. The following parameters were used for documentation: 6 channel
EEG (including C3 and C4 to mastoid); EOG (2 channels), respiration (nasal and oral
thermistor, pulse oximeter, thoracic and abdominal respiratory inductance plethysmography,
snore sensor and airflow measurement with pressure transducer airflow sensors), and
bilateral EMGs of the musculus masseter and musculus tibialis anterior. A one-channel ECG
was recorded. Polysomnography was performed under continuous observation by trained
medical staff.
The patient showed REM sleep without atonia (RSWA) during polysomnography (Fig. 2).
RBD diagnosis was based on the presence of RSWA and dream enactment behaviors (DEB)
in the absence of EEG epileptiform abnormality during REM sleep in accordance with the
International Classification of Sleep Disorders (2nd edition) (American Academy of Sleep

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Medicine, 2005). RSWA was defined as the presence of sustained tonic activity (increased
chin EMG amplitude during greater than 50% of an epoch) and excessive phasic activity (at
least 5, three-second epochs containing transient bursts of muscle activity) during a 30second epoch of REM sleep.
3.2. Participants
The patient underwent rs-fcMRI 32 months after the onset of his symptoms. At this time his
complex visual hallucinations had resolved, although, he experienced pareidolias, illusions
in dim lighting, and approximately eight daily episodes of ‘passage’ hallucinations in his
lateral visual field. The patient did not report perceptual events during the scanning session.

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Resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) data were
gathered in the patient and 27 Controls (15 women; age = 25.6 ± 5.0 years (mean ± SD)).
Participants were right-handed native English speakers. All volunteers had no history of
neurological or psychiatric illness. To ensure our findings could not be accounted for by age
effects, or differences in imaging acquisition parameters, an independent group of 16
healthy, age-matched right-handed Older Controls (8 women; age = 62.0 ± 10.9 years) was
recruited from a separate institution. To control for potential changes in cerebral blood flow
or functional connectivity previously reported in patients with obstructive sleep apnea
(OSA) (Durgan & Bryan, 2012; Zhang et al., 2012), we recruited 3 right-handed OSA
Controls (3 men; age = 58.0 ± 6.1 years). All OSA Controls had previously undergone
diagnostic in-hospital polysomnography. Two of the OSA Controls were compliant with
CPAP therapy and all endorsed at least three (of four) symptoms on the OSA STOP
questionnaire (Chung et al., 2008).

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All Older and OSA Controls scored at least 26/30 on the Montreal Cognitive Assessment
(Nasreddine et al., 2005). All participants provided written, informed consent prior to
participation in the study, in accordance with the Declaration of Helsinki. The Partners
Institutional Review Board and the MIT committee on the use of humans as experimental
subjects (COUHES) approved the study protocol.
3.3. MRI data acquisition

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Functional magnetic resonance imaging (fMRI) data from the patient were acquired using a
3-Tesla Siemens Magnetom Verio scanner (Siemens, Munich, Germany) paired with a 12channel phased-array whole-head coil. Motion was reduced with foam pillows. T1-weighted
magnetization-prepared rapid acquisition with gradient echo (MPRAGE) anatomical images
were collected with the following parameters: time repetition (TR) = 1800 ms, time echo
(TE) = 2.95 ms, flip angle (FA) = 12°, 160 slices, 0.78 × 0.78 × 1 mm resolution. Functional
T2*-weighted images were gathered over two sessions of 5 minutes using echo-planar
imaging (EPI) sensitive to blood oxygenation level-dependent (BOLD) contrast with the
following parameters: TR = 2000 ms, TE = 30 ms, FA = 90°, 30 axial slices, ascending
sequence, 3.44 × 3.44 × 4 mm resolution. The patient and controls were instructed to remain
still and alert with eyes closed during the scanning. To allow for T1-equilibration effects, 10
dummy volumes were discarded prior to acquisition.

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Imaging data from Controls were obtained using a 3 Tesla GE Signa system (General
Electric, Milwaukee, WI, USA). Whole brain T1-weighted axial 3D spoiled gradient
recalled (SPGR) structural images were acquired using array spatial sensitivity encoding
technique (ASSET, i.e., parallel imaging) and an 8-channel head coil (TR = 7.8 ms, TE = 3.0
ms, flip angle = 20°, 176 slices, 0.5 × 0.5 × 1 mm resolution). BOLD functional images
were acquired over 7 minutes using single-shot gradient-echo EPI and a standard quadrature
head coil (TR = 2000 ms, TE = 40 ms, FA = 90°, 27 axial slices, ascending sequence, 2 × 2
× 4 mm resolution).

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FMRI data from Older Controls and OSA Controls were gathered using a 3-Tesla Siemens
Tim Trio scanner paired with a 32-channel head coil. T1-weighted MPRAGE anatomical
images were obtained: TR = 2530 ms, TE = 3.39 ms, FA = 7.0°, 176 slices, 1 mm isotropic
resolution. Resting state T2*-weighted images were obtained with an ascending EPI
sequence: TR = 2500 ms, TE = 30 ms, FA = 90°, 30 slices, 150 volumes, 6.5 minutes, 3.1 ×
3.1 × 3.4 mm resolution.
3.4. Data preprocessing

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Resting state data were preprocessed in SPM8 (Wellcome Department of Imaging
Neuroscience, London, UK; http://www.fil.ion.ucl.ac.uk/spm). Preprocessing procedures
included: (1) slice-timing correction; (2) rigid body motion correction by realigning all
images to the first image of the functional run; (3) segmentation and normalization of the
structural images to the Montreal Neurological Institute/International Consortium for Brain
Mapping (MNI/ICBM) 152 template; (4) normalization of the functional images based on
the structural normalization matrix; (5) artifact detection and rejection using the art tool
(http://www.nitrc.org/projects/artifact_detect); and (6) spatial smoothing with an isotropic 6
mm full-width at half-maximum (FWHM) Gaussian kernel.
3.5. Analysis
Rs-fcMRI analysis was performed using a seed-based approach with in-house, custom
software ‘Conn toolbox’ (http://www.nitrc.org/projects/conn) (Whitfield-Gabrieli & NietoCastanon, 2012). Physiological and other sources of noise were estimated using the
aCompcor method (Behzadi, Restom, Liau, & Liu, 2007) and regressed out together with
movement-related and artifactual covariates. The residual BOLD time series was band-pass
filtered (0.009 - 0.08 Hz) and linearly detrended.

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To examine brainstem-geniculate, geniculate-occipital and brainstem-occipital functional
connectivity, we performed ROI-to-ROI analyses using a priori anatomically defined
regions-of-interest. To determine the specificity of findings, we compared the functional
connectivity of the focal lesion in the left rostrodorsal pons to a right homologous nonlesioned rostrodorsal pons. Left and right pontine ROI were drawn by an expert rater on the
patient’s T1-weighted structural image in fslview, and normalized to the MNI standard brain
(Fig. 3A). To ensure that the lesioned left rostrodorsal pons was comprised of functional
neural tissue, we compared the time-series signal-to-noise ratio (tSNR) in left and right
rostrodorsal pontine ROI in the patient versus controls. tSNR from these seeds was

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calculated as the ratio of mean SNR over the time-series standard deviation from preprocessed EPI data (Triantafyllou, Polimeni, & Wald, 2011).
The bilateral lateral occipital cortices ROI was generated by FreeSurfer segmentation of the
MNI/ICBM 152 template (Fig. 3B). The bilateral lateral geniculate nuclei (LGN) ROI was
based on a functional anatomical study where flickering checkerboard stimuli were used to
identify mean peak activations in right and left LGN across nine healthy participants
(Kastner et al., 2004). We generated 5 mm radius spheres around these peak functional
coordinates to define the LGN ROI (MNI x, y, z: 23, -21, -10 (right); -22, -22, -10 (left))
(Fig. 3B).

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First-level correlation maps were obtained by extracting the residual BOLD time course
from each ROI and calculating Pearson’s correlation coefficients between this time course
and the time course of all other brain voxels. Correlation coefficients were Fisher
transformed to ‘z’ scores to increase normality prior to second-level General Linear Model
analyses. We interrogated each ROI by extracting the mean z-value for all participants. We
applied single-case methodology developed by Crawford and Howell (1998) to test for
significant functional connectivity differences in mean z-values between the patient and
controls. To control for potential OSA-related confounds in the patient, we assessed
functional connectivity in the three OSA controls compared to all other controls using the
non-parametric Mann-Whitney test. Significance was set at p < .05, two-tailed.

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To identify brain regions with paradoxically increased coupling to lateral occipital cortex in
the patient greater than controls, we performed an exploratory seed-to-voxel analysis,
corrected for multiple comparisons. We tested for differences (patient versus controls) by
performing a whole-brain seed-to-voxel analysis using a two-sample t-test. Clusters were
significant at a false discovery rate (FDR) cluster-corrected threshold of p < .05. We
interrogated the resulting significant cluster qualitatively by extracting the mean z-value for
all participants.

4. Results

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The patient had minimal mean movement in all directions (x = 0.016 mm; y = 0.118 mm; z
= 0.099 mm; pitch = 0.052 degrees; roll = 0.012 degrees; yaw = 0.023 degrees) and no scanto-scan movement outliers over 2mm. Despite diversity in imaging acquisition parameters,
we identified consistent functional connectivity differences between the patient and Controls
or Older Controls. Thus, our findings cannot be explained by potential differences in SNR.
Similarity and reliability of rs-fcMRI results across different scanners and acquisition
parameters have been shown previously (Jann et al., 2015; Van Dijk et al., 2010). There was
no significant difference in tSNR between right (non-lesioned) and left (remotely lesioned)
rostrodorsal pons in the patient versus controls supporting the functionality of neural tissue
at the site of the remote stroke (right versus left difference: patient 3.1, controls 2.3 ± 23.4;
Crawford significance test, t = 0.2, p = 0.8).
Unlike controls, the patient displayed a positive correlation between the left pontine ROI and
lateral occipital cortices (Older Controls mean z-value -0.023 (SD 0.07); Controls mean zvalue -0.017 (SD 0.06); patient z-value 0.192). To test for a difference in functional
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connectivity, we conducted a two-tailed Crawford single-case significance test that accounts
for control sample size (Crawford & Howell, 1998). This revealed a significant increase in
functional connectivity between the left rostrodorsal pons and the lateral occipital cortices in
the patient compared to Controls (t = 3.5, p = 0.002); an identical analysis also showed
significantly enhanced functional connectivity in the patient compared to Older Controls (t =
3.0, p = 0.008) (Fig. 4).

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To test for disruption in brainstem-geniculate connectivity, we again applied the Crawford
test to the mean z-values extracted from the left rostrodorsal pons to LGN ROI (Older
Controls mean z-value 0.004 (SD 0.08); Controls mean z-value 0.072 (SD 0.09); patient zvalue -0.26). This revealed significantly decreased functional connectivity between left
rostrodorsal pons and LGN in the patient versus Controls (t = 3.5, p = 0.002) and between
the patient and Older Controls (t = 3.3, p = 0.005) (Fig. 4). Critically, there was also
significantly decreased geniculate-occipital functional connectivity in the patient compared
to Controls (t = 2.9, p = 0.007) and Older Controls (t = 2.5, p = 0.023) (Older Controls mean
z-value 0.004 (SD 0.07); Controls mean z-value -0.002 (SD 0.06); patient z-value -0.183)
(Fig. 4). Two exploratory, whole-brain seed-to-voxel analyses from left rostrodorsal pons
and LGN demonstrated similar findings (see Supplemental Materials).

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To assess the specificity of the left pontine connectivity findings, we performed identical
functional connectivity analyses from the right, non-lesioned rostrodorsal pontine ROI.
There was no difference in right pontine to LGN functional connectivity in the patient versus
controls (Older Controls mean z-value 0.036 (SD 0.08); Controls mean z-value 0.067 (SD
0.1); patient z-value -0.02; all p > 0.38). Similarly, there was no difference in right pons to
lateral occipital functional connectivity in the patient compared to controls (Older Controls
mean z-value -0.015 (SD 0.08); Controls mean z-value -0.007 (SD 0.07); patient z-value
0.036; all p > 0.53). In addition, controls showed no difference between left versus right
rostrodorsal pons to LGN connectivity (two-sample t-test, t = 0.2, p = 0.8) and no difference
in left versus right rostrodorsal pons to lateral occipital connectivity (two-sample t-test, t =
0.4, p = 0.7).
The patient’s pattern of functional connectivity did not resemble that of the OSA Controls,
suggesting that our findings are not confounded by comorbid OSA in the patient (Fig. 4).
There was no significant difference in ponto-geniculate-occipital functional connectivity in
OSA Controls compared to all other controls (Mann-Whitney, ponto-occipital: U = 54.0, p =
0.6; ponto-geniculate: U = 35.0, p = 0.2; geniculate-occipital: U = 61.0, p = 0.9).

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An exploratory, whole-brain seed-to-voxel analysis, corrected for multiple comparisons,
showed significantly increased functional connectivity in the patient versus controls between
the lateral occipital ROI and two clusters within prefrontal cortex (PFC) (Fig. 5). The largest
cluster was located in left orbitofrontal cortex (OFC) (peak MNI x, y, z coordinates: -18, 16,
-12; spatial extent: 633 voxels; p = 0.03, cluster-level, FDR-corrected). A second cluster was
identified in bilateral supplementary eye field (SEF) and supplementary motor area (SMA)
(peak MNI x, y, z coordinates: 2, -8, 76; spatial extent: 547 voxels; p = 0.03, cluster-level,
FDR-corrected).

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5. Discussion
We present a patient with acute-onset PH and RBD associated with a left rostrodorsal
pontine ischemic stroke. We applied combined lesional and resting-state fMRI methodology
to examine the distributed network effects of the patient’s brainstem lesion in the chronic
stage. We found significantly decreased functional connectivity between left rostrodorsal
pons and LGN, and between LGN and visual association cortices in the patient compared to
controls. In contrast, functional connectivity was significantly enhanced between visual
association cortices and left rostrodorsal pons, and between visual association cortices and
PFC in the patient versus controls. This case highlights a putative shared neural substrate
underlying visual hallucinations and RBD, two syndromes that commonly coexist in
neurodegenerative alpha-synucleinopathies that involve brainstem synuclein deposition and
degeneration.

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Our patient had focal damage to rostrodorsal pons, encompassing multiple nuclei including
locus coeruleus (LC), ventrolateral periaqueductal gray matter (vlPAG), and lateral pontine
tegmentum (LPT) (Boeve et al., 2007). These brainstem regions modulate arousal and
attention, REM behavioral state switching, and thalamocortical excitability (Boeve et al.,
2007; Lu, Sherman, Devor, & Saper, 2006; Rogawski & Aghajanian, 1980; Sara, 2009).
Disruption of these processes may underlie coexistent RBD and PH in this patient. In
rodents, LC sends inhibitory noradrenergic inputs to visual cortex that improve perceptual
acuity by gating target neurons (Hurley, Devilbiss, & Waterhouse, 2004; Sara, 2009). The
patient had paradoxically augmented coupling between pons and visual association cortex.
This could reflect dysfunctional “gain modulation” of LC on visual cortex, shifting the
probability of spontaneous oscillations and integrative properties of cortical neurons (Haider,
Duque, Hasenstaub, Yu, & McCormick, 2007; Sara & Bouret, 2012). Nonvisual brainstem
regions (including vlPAG and LC) also project to LGN and thalamic reticular nucleus
(Mackay-Sim, Sefton, & Martin, 1983; Rogawski & Aghajanian, 1980). The patient’s
diminished LGN functional connectivity may reflect disruption of thalamocortical loops and
altered firing of inhibitory interneurons within LGN itself (Sherman & Guillery, 2001).
Thus, a lesion in the vicinity of LC may alter tuning of retino-geniculate-occipital circuits
and simultaneously influence sleep and visual pathways.

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Related to our main finding, Purkinje hallucinations are associated with diminished
connectivity between LGN and cortex accompanied by increased occipito-temporal
connectivity (ffytche, 2008). A putative mechanism for this dissociation is a shift in the
mode of thalamocortical firing from tonic (where retinal inputs are accurately transmitted to
cortex) to burst mode (where there is non-linear summation of retinal inputs in visual cortex)
(ffytche, 2008; Sherman, 2001). Burst mode is induced by thalamic de-afferentation and is
associated with diminished thalamic and increased cortical metabolic demand (Llinás,
Ribary, Jeanmonod, Kronber, & Mitra, 1999). This mechanism may also underlie an array of
positive symptoms in neurological/neuropsychiatric conditions, termed ‘thalamocortical
dysrhythmias’ (ffytche, 2008; Jeanmonod, Magnin, & Morel, 1996; Llinás, Ribary,
Jeanmonod, Kronber, & Mitra, 1999).

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Hallucinations and illusions fall along a continuum: although this patient’s well formed
visual hallucinations resolved, he reported persistent visual illusions, pareidolias and
‘passage’ hallucinations. RBD, visual misperceptions and hallucinations are important nonmotor features of neurodegenerative synucleinopathies including Parkinson’s disease (PD)
and Lewy body dementia (LBD) (Onofrj et al., 2013; Shine et al., 2014; Uchiyama et al.,
2012). The coexistence of these syndromes secondary to a pontine lesion suggests a shared
underlying neural mechanism. Convergent evidence suggests that brainstem alpha-synuclein
deposition in LBD and PD contributes to development of visual hallucinations (Manford &
Andermann, 1998; Onofrj et al., 2013). Relatedly, RBD in PD or LBD is associated with a
lower Braak stage and independently predicts the development of hallucinations (Arnulf,
2013; Dugger et al., 2012). In the early stages of PD 20 to 45% of patients report fleeting
sideway shadows (‘passage’ hallucinations) or a sensation of presence (Fénelon, Soulas,
Cleret de Langavant, Trinkler, & Bachoud-Levi, 2011; Fénelon, Soulas, Zenasni, & de
Langavant, 2010; Mack et al., 2012). Pareidolias and visual hallucinations are common in
patients with LBD (Uchiyama et al., 2012). Patients with PD and visual hallucinations also
show altered functional connectivity in attentional networks and structural changes in
visuoperceptual pathways (Goldman et al., 2014; Shine et al., 2014). Based on the findings
in this patient, we hypothesize that altered functional connectivity in PD patients with
hallucinations may occur via altered LC inputs to attentional networks. This hypothesis is
consistent with human fMRI and EEG data that show coupling between LC and the ventral
attention network (Walz et al., 2013).

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The patient showed increased coupling between visual association cortex and left
orbitofrontal cortex (OFC), a region that plays an important role in top-down visual
processing. The patient’s pareidolias might be explained in light of this finding. OFC is key
in generating expectations about image content (Bar et al., 2006) and signal propagation
from OFC to visual cortex facilitates object recognition (Bar et al., 2006; O’Shea & Walsh,
2006; Petrides, Alivisatos, & Frey, 2002; Trapp & Bar, 2015). Aberrant OFC to visual
association cortex connectivity could impede the mapping of internally generated
predictions onto incoming visual information and impair rapid processing of ambiguous
visual stimuli. OFC is structurally connected to occipital cortex via the inferior frontooccipital fasciculus (IFOF) (Forkel et al., 2014). Altered structural integrity of IFOF is
associated with visual hallucinations in schizophrenia (Amad et al., 2014; Ćurčić-Blake et
al., 2015). Relatedly, intraoperative stimulation of PFC produces visual hallucinations
(Vignal, Chauvel, & Halgren, 2000) and frontal leucotomy can improve or abolish visual
hallucinations (McLardy & Meyer, 1949).

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The patient also demonstrated enhanced functional connectivity between visual association
cortex and supplementary eye field (SEF). SEF is a region at the pre-SMA/SMA boarder
with extensive PFC connectivity that supplies second-order neurons to middle temporal area
(MT) of the dorsal visual stream (Grosbras, Lobel, Van de Moortele, LeBihan, & Berthoz,
1999; Ninomiya, Sawamura, Inoue, & Takada, 2012; Tehovnik, Sommer, Chou, Slocum, &
Schiller, 2000). SEF is associated with executive control of saccades, motion perception and
monitoring of visual search (Purcell, Weigan, & Schall, 2012). During kinematic
stimulation, PD patient with visual hallucinations show hyperactivation of SEF (Stebbins et
al., 2004). Diederich, Stebbins, Schiltz, and Goetz (2014) hypothesized that deficient
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corollary discharges to the frontal eye field and reduced integrity of the retino-geniculateextrastriate (MT/V5) system cause ‘passage’ hallucinations in PD. We propose that a similar
mechanism underlies the passage hallucinations reported by the patient.

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Although sleep disturbances are common in peduncular hallucinosis (Manford &
Andermann, 1998), to our knowledge coexistent RBD and PH were reported in only one
prior case (Vetrugno et al., 2009) in whom SPECT revealed hyperperfusion in lateral
occipital cortex and PFC during visual hallucinations, similar to our findings. There are a
handful of lesional RBD cases secondary to multiple sclerosis, vascular malformation,
stroke, and cerebral vasculitis (Boeve et al., 2007; Iranzo & Aparicio, 2009; St Louis et al.,
2014). Lesional studies in rodents and humans suggest that mutually inhibitory ‘REM on’
and ‘REM off’ brainstem systems regulate sleep states (Lu et al., 2006). Our patient’s
rostrodorsal pontine lesion putatively encapsulates key ‘REM off’ brainstem regions
including LPT, vlPAG, and LC (Boeve et al., 2007). In rodents, vlPAG and LPT receive
excitatory noradrenergic projections from LC, and lesions to these regions increase the
amount of REM sleep (Lu et al., 2006). Although LC is quiescent during REM sleep,
patients with PD and RBD show reduced structural integrity of LC (Garcia-Lorenzo et al.,
2013). It is controversial whether visual hallucinations in PD represent REM intrusions
during wakefulness (Arnulf et al., 2000; Arnulf, 2013; Manni et al., 2011; Nomura et al.,
2003).

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One potential concern is the use of a stroke site as a region of interest. However, certain
features of this case justify the use of the left pontine ROI: the brainstem lesion was small,
chronic, and showed no residual T2-weighted changes on structural imaging. Critically,
there was a high time-series signal-to-noise ratio (tSNR) within the lesion and no difference
in tSNR in the left (lesioned) compared to the right (non-lesioned) rostrodorsal pons. Based
on this finding, and given the patient’s persistent symptoms, we hypothesize that the left
rostrodorsal pontine lesion encompasses dysfunctional rather than non-functional neural
tissue. Relatedly, the lack of connectivity changes from the right pontine ROI support the
specificity of our findings.
In summary, this study supports the application of rs-fcMRI to characterize the distributed
network impacts of focal brain injury in individuals. We identified a pattern of altered
functional connectivity suggestive of thalamic de-afferentation and reorganization of the
visual network secondary to rostrodorsal pontine damage. This case enhances our
understanding of brainstem modulation of geniculate-occipital pathways. Our approach may
help identify novel, individualized therapeutic cortical targets for non-invasive
neurostimulation.

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Acknowledgments
The Richard and Edith Strauss Fellowship in Clinical Medicine and the Canadian Institutes of Health Research
Fellowship to M.R.G. supported this work. We are grateful to Laura Rigolo for help with participant recruitment
and to Dr. Jitendra Sharma for helpful discussions. We thank the patient for his participation and consent to research
related to this case.

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Fig. 1.

Peduncular hallucinosis and REM sleep behavior disorder associated with ischemic pontine
infarction. In the left rostrodorsal pons, diffusion-weighted imaging (DWI) shows high
signal and apparent diffusion coefficient (ADC) map reveals low signal suggestive of an
acute ischemic stroke.

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Fig. 2.

Patient polysomnography during REM sleep. There is persistent muscle activity in chin
(musculus masseter) and leg (tibialis anterior) EMG leads during REM sleep indicative of
REM sleep without atonia.

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Fig. 3.

A priori regions of interest (ROIs). (A) Left (blue) and right (red) rostrodorsal pontine ROI
displayed on an axial T1-weighted image of the patient’s brainstem. (B) Bilateral lateral
geniculate nuclei ROI (red) and lateral occipital cortices ROI (blue).

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Fig. 4.

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Dissociated patterns of functional connectivity in the ponto-geniculate-occipital system in
the patient versus controls. There is significantly increased resting-state functional
connectivity between left rostrodorsal pons and lateral occipital ROI in the patient compared
to controls. Conversely, the patient shows significantly reduced functional connectivity
between left rostrodorsal pons and lateral geniculate nuclei (LGN), and also between LGN
and lateral occipital cortices. Obstructive sleep apnea (OSA) Controls do not show
significant differences in functional connectivity compared to all other controls. The
schematic diagram (bottom right) depicts the change in functional connectivity between ROI
in the patient compared to controls (red = reduction; green = augmentation).

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Fig. 5.

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Increased funcitonal connectivity between lateral occipital and prefrontal cortices in the
patient versus controls. This exploratory, cluster-corrected seed-to-voxel analysis revealed
significantly increased coupling between bilateral lateral occipital cortices and left
orbitofrontal cortex (OFC), and between lateral occipital cortices and supplementary eye
field in the patient. The mean z-value extracted from the OFC cluster is shown in the graph
and is greater in the patient than the controls.

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